Unadilla, GA
How exposed is Unadilla to wildfire?
Unadilla sits at the 53rd percentile nationally for wildfire risk to structures — modestly above the national average for wildfire risk — per USFS's Wildfire Risk to Communities model, built from its 1,026 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Unadilla at the 53rd national percentile — 0 points above its risk-to-structures score, a gap driven by how much is actually built there.
Where Unadilla's buildings actually sit
USFS classifies 47.1% of Unadilla's buildings as Direct exposure, higher than its 39.7% Indirect share and far above its 13.3% Minimal share — a profile where 483 structures sit close enough to vegetation that lot clearing matters most.
Unadilla against the rest of the country
Inside Georgia, Unadilla sits at just the 9th percentile even though it scores 53rd nationally — the state's overall wildfire exposure is high enough to make this a relatively quiet corner of it. Among the 31,521 US communities USFS scores, Unadilla ranks 14,900 for wildfire risk (1 is highest) and 11,750 by building count (1 is largest). Within Georgia alone, it ranks 610 of 669 places by risk. See the full county-by-county picture for Georgia on its state page.
What this risk score means for insurance
Unadilla's elevated rating (53rd percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.
Hardening a home in Unadilla
Because Direct exposure dominates in Unadilla (47.1%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Unadilla's figures come from
Every one of the two percentiles behind Unadilla's 14,900-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Unadilla's dominant direct exposure actually means, with real examples from across the dataset.